Person-centred care as an evolving field of research: a scoping review
Bibliographic record
Abstract
Introduction: Changes in policy towards a healthcare approach viewing patients as persons provide calls for person-centred healthcare practices. The objective of this scoping review was to present an overview of the international literature on PCC. Methods: Database-specific search string including index terms and free text words related to PCC were constructed to identify relevant literature indexed in PubMed, Scopus, PsychINFO, CINAHL and Web of Science. Two different methods of combined manual and computer-assisted screening were applied to identify citations to be included in the review. Results: In total, 1,351 publications were included, whereof theoretical and empirical studies were most prevalent in the sample. For the latter, the most common setting was hospital care. The study population was most often health professionals or patients. The most frequently used term was patient-centred, followed by person-centred and family-centred. Research from six continents was included. An exploration of collaborations and research clusters has revealed several clusters. Discussion: This review provides a snapshot of the literature on PCC. The lack of clarity in terminology presents barriers to comprehensively overviewing the vast amount of available research within the field, which in turn presents challenges for research-based policy and practice development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.019 | 0.026 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".